The application of large language models (LLMs) to specialized fields, such as Satellite Communications (SatCom), presents unique challenges due to the extensive and cutting-edge knowledge required. We present a fine-tuning approach for adapting 7-billion-parameter instructed LLMs (Llama-3v and Mistral) to SatCom, using a proprietary corpus sourced from the European Space Agency (ESA)...
Recent advances in artificial intelligence have transformed the landscape of cybersecurity research, particularly through intelligent agent-based simulations and large language models (LLMs). Traditional cybersecurity datasets are often static and outdated, limiting the capacity to train adaptive AI systems. To address this, we developed a dynamic synthetic simulation framework that transforms...
Foundation models plus ample compute make many “moderate” vision tasks solvable with minimal custom code. This talk introduces an LLM-steerable pipeline that compiles a brief YAML spec into end-to-end segmentation, zero-shot classification, and optional geometry checks, executed on GPU clusters.
A remote multimodal LLM (e.g., ChatGPT) generates the configuration based on sample images and...
Archaeological site detection is entering a new era thanks to advances in remote sensing and artificial intelligence. Archaeological sites such as hillforts often have irregular and complex shapes, making them challenging to identify using conventional computer vision methods. Multimodal approaches that combine LiDAR-derived LRM images with aerial orthoimagery improve detection accuracy, but...
This presentation explores how Large Language Models (LLMs) enhance Optical Character Recognition (OCR) pipelines through contextual text correction, document understanding, semantic labeling, and information extraction. It will also highlight real-world use cases such as automated document processing, invoice and receipt parsing, identity verification, and multilingual text recognition.
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